What is a qualitative survey?
A practical guide for performing a qualitative survey
For more best practices see our method overview
Definition of a qualitative survey
A qualitative survey is a type of research method that aims to explore the meanings, perceptions, and experiences of a specific population. Unlike quantitative surveys, which rely on standardized questions and numerical data, qualitative surveys use open-ended questions and textual data to capture the richness and diversity of the respondents’ views. Qualitative surveys can be used for various purposes, such as exploring new topics, generating hypotheses, evaluating programs, or informing policy decisions.
In the following, we will explain how to perform a qualitative survey. This guideline is aligned with the guideline proposed by Jansen (2010). The description provided by Jansen is purpusefully flexible regarding the employed methods for qualitative data analysis (QDA) as well as the types of data to gather. In this article we will be slightly more prescriptive while pointing towards options for flexbility along the way.
We cover the following steps:
We cover the following steps:
- Define the research question and objectives
- Design the sampling strategy and recruit the respondents
- Develop the survey instrument and pilot test it
- Conduct the data collection and ensure quality control
- Analyze the data and report the findings
Process of a qualitative survey
Step 1:
Define the research question and objectives
The first step in any research project is to define the research question and objectives. This will help you to clarify the purpose and scope of your study, as well as the expected outcomes and implications. The research question should be clear, focused, and relevant to the topic of interest. The objectives should be specific, measurable, achievable, realistic, and time-bound.
Example of a research question for a qualitative survey
If you are interested in studying the attitudes of college students toward online learning during the COVID-19 pandemic, your research question could be: How do college students perceive and experience online learning during the COVID-19 pandemic? Your objectives could be:- To explore the advantages and disadvantages of online learning from the students’ perspective
- To identify the factors that influence the students’ satisfaction and motivation with online learning
- To provide recommendations for improving the quality and effectiveness of online learning
Step 2:
Design the sampling strategy and recruit the respondents
The next step is to design the sampling strategy and recruit the respondents for your study. Sampling refers to the process of selecting a subset of individuals from a larger population that represents the characteristics and diversity of that population. There are two main types of sampling: statistical sampling and purpuseful sampling.
Statistical sampling (probability sampling) involves selecting individuals randomly from a population, so that each individual has an equal chance of being included in the sample. This ensures that the sample is representative of the population and allows for generalization of the findings. Random sampling helps mitigate selection bias and researcher bias. However, statistical sampling requires a complete list of all individuals in the population, which may not be available or feasible for some studies.
Purpuseful sampling (non-statistical sampling) involves selecting individuals based on some criteria or convenience, rather than randomly. This allows for more flexibility and accessibility in choosing the sample, but it may introduce bias and limit transferability of the findings. Purpuseful sampling includes techniques such as polar sampling, theoretical sampling, quota sampling, snowball sampling, and convenience sampling.
For qualitative surveys, purpuseful sampling is more commonly used, as it allows for selecting individuals who can provide rich and relevant information about the topic of interest. Qualitative researchers often consider theoretical sampling as an ideal strategy because its flexibility allows for steering the sampling towards the things that are most interesting or where gaps in the theory occur. However, it is important to ensure that the sample is sufficiently large and diverse to capture the range of views and experiences of the population.
To recruit respondents for your study, you need to obtain their informed consent and explain the purpose, procedures, risks, benefits, confidentiality, and voluntary nature of your study. You may also need to provide them with incentives or compensation for their participation, such as money, gift cards, or course credits. However, be sure to not create undue incentives that may introduce Self-Selection Bias because participants who participate purely because they need the money may not be a good sample. From an ethical perspective you also should not provide incentives that would lead participants to agree to risk that they would otherwise not take on. Be sure to document all of these decisions in your audit trail.
Statistical sampling (probability sampling) involves selecting individuals randomly from a population, so that each individual has an equal chance of being included in the sample. This ensures that the sample is representative of the population and allows for generalization of the findings. Random sampling helps mitigate selection bias and researcher bias. However, statistical sampling requires a complete list of all individuals in the population, which may not be available or feasible for some studies.
Purpuseful sampling (non-statistical sampling) involves selecting individuals based on some criteria or convenience, rather than randomly. This allows for more flexibility and accessibility in choosing the sample, but it may introduce bias and limit transferability of the findings. Purpuseful sampling includes techniques such as polar sampling, theoretical sampling, quota sampling, snowball sampling, and convenience sampling.
For qualitative surveys, purpuseful sampling is more commonly used, as it allows for selecting individuals who can provide rich and relevant information about the topic of interest. Qualitative researchers often consider theoretical sampling as an ideal strategy because its flexibility allows for steering the sampling towards the things that are most interesting or where gaps in the theory occur. However, it is important to ensure that the sample is sufficiently large and diverse to capture the range of views and experiences of the population.
Example of a sampling strategy for a qualitative survey
If you are studying the attitudes of college students toward online learning during the COVID-19 pandemic, you could use purposive sampling to select students who have participated in online learning during this period. You could also use quota sampling to ensure that your sample reflects the proportions of different groups in your population, such as gender, age, major, or academic performance.To recruit respondents for your study, you need to obtain their informed consent and explain the purpose, procedures, risks, benefits, confidentiality, and voluntary nature of your study. You may also need to provide them with incentives or compensation for their participation, such as money, gift cards, or course credits. However, be sure to not create undue incentives that may introduce Self-Selection Bias because participants who participate purely because they need the money may not be a good sample. From an ethical perspective you also should not provide incentives that would lead participants to agree to risk that they would otherwise not take on. Be sure to document all of these decisions in your audit trail.
Step 3:
Develop the survey instrument and pilot test it
The survey instrument is the tool that you use to collect data from your respondents. For qualitative surveys, this usually consists of a set of open-ended questions that allow respondents to express their opinions and experiences in their own words. The questions should be clear, concise, relevant, unbiased, and respectful. They should also cover all aspects of your research question and objectives.
To develop your survey instrument, you can use existing literature or previous studies as a source of inspiration or reference. You can also consult experts or stakeholders in your field for feedback or suggestions. You should avoid using leading or suggestive questions that may influence or limit respondents’ responses. You should also avoid using jargon or technical terms that may confuse or alienate respondents.
To ensure that your survey instrument is valid and reliable, you need to pilot test it with a small group of respondents who are similar to your target population. Pilot testing allows you to check if your questions are clear, understandable, appropriate, and comprehensive. Already in the pilot study you should use member checking to generate feedback. It also allows you to identify any problems or issues with your survey instrument and make necessary revisions before conducting your main data collection.
You could pilot test your survey instrument with a sample of 10 to 20 students who have participated in online learning during the COVID-19 pandemic. You could ask them to complete your survey instrument and provide feedback on the clarity, relevance, and comprehensiveness of your questions. You could also ask them to suggest any additional questions or topics that they think are important or interesting to explore.
To develop your survey instrument, you can use existing literature or previous studies as a source of inspiration or reference. You can also consult experts or stakeholders in your field for feedback or suggestions. You should avoid using leading or suggestive questions that may influence or limit respondents’ responses. You should also avoid using jargon or technical terms that may confuse or alienate respondents.
To ensure that your survey instrument is valid and reliable, you need to pilot test it with a small group of respondents who are similar to your target population. Pilot testing allows you to check if your questions are clear, understandable, appropriate, and comprehensive. Already in the pilot study you should use member checking to generate feedback. It also allows you to identify any problems or issues with your survey instrument and make necessary revisions before conducting your main data collection.
Example of a survey instrument for a qualitative survey
If you are studying the attitudes of college students toward online learning during the COVID-19 pandemic, you could develop a survey instrument that includes questions such as:- How do you feel about online learning in general?
- What are the main advantages and disadvantages of online learning for you?
- How satisfied are you with the quality and effectiveness of online learning during the COVID-19 pandemic?
- How motivated are you to participate and engage in online learning during the COVID-19 pandemic?
- What are the main challenges or difficulties that you face with online learning during the COVID-19 pandemic?
- How do you cope with these challenges or difficulties?
- What are the main factors that influence your satisfaction and motivation with online learning during the COVID-19 pandemic?
- How do you think online learning could be improved or enhanced during the COVID-19 pandemic?
- How do you think online learning will affect your academic performance and future prospects?
You could pilot test your survey instrument with a sample of 10 to 20 students who have participated in online learning during the COVID-19 pandemic. You could ask them to complete your survey instrument and provide feedback on the clarity, relevance, and comprehensiveness of your questions. You could also ask them to suggest any additional questions or topics that they think are important or interesting to explore.
Step 4:
Conduct the data collection and ensure quality control
The data collection is the process of administering your survey instrument to your respondents and obtaining their responses. For qualitative surveys, this can be done through various methods, such as face-to-face interviews, telephone interviews, online surveys, email surveys, or focus groups. The choice of method depends on your research question, objectives, resources, and preferences.
To ensure quality control of your data collection, you need to follow ethical principles and guidelines for conducting research with human subjects. You need to protect the privacy and confidentiality of your respondents and their data. You need to obtain their informed consent and respect their rights and dignity. You need to avoid any harm or deception to your respondents. You also need to ensure that your data collection is consistent, accurate, and complete.
To achieve this, you need to:
Example of data collection for a qualitative survey
If you are studying the attitudes of college students toward online learning during the COVID-19 pandemic, you could use online surveys as a method of data collection, as they are convenient, accessible, and cost-effective for both you and your respondents. You could use a platform such as SurveyMonkey or Qualtricsto create and distribute your survey instrument to your respondents via email or social media. You could also use a platform such as Zoomor Skypeto conduct video interviews or focus groups with your respondents if you want to obtain more in-depth and interactive data.To ensure quality control of your data collection, you need to follow ethical principles and guidelines for conducting research with human subjects. You need to protect the privacy and confidentiality of your respondents and their data. You need to obtain their informed consent and respect their rights and dignity. You need to avoid any harm or deception to your respondents. You also need to ensure that your data collection is consistent, accurate, and complete.
To achieve this, you need to:
- Use a secure and reliable platform or software for creating and administering your survey instrument
- Provide clear and detailed instructions and information for your respondents
- Monitor and track the response rate and completion rate of your survey instrument
- Follow up with non-respondents or incomplete to be aware of potential non-response bias
- Check and verify the validity and reliability of your respondents’ data
- Store and backup your respondents’ data safely and securely
Step 5:
Analyze the data
The data analysis is the process of examining, interpreting, and presenting your respondents’ data. For qualitative surveys, this involves identifying, coding, categorizing, and synthesizing themes, patterns, and meanings from your respondents’ textual data. There are various methods and techniques for analyzing qualitative data, such as content analysis, Thematic Analysis, narrative analysis, discourse analysis, or Grounded Theory.
To analyze your data, you can use manual or computer-assisted methods. Manual methods involve reading, reviewing, and coding your data by hand using tools such as highlighters, sticky notes, or spreadsheets. Computer-assisted methods involve using software such as QDAcity to organize, manage, and analyze your data electronically.
To analyze your data, you can use manual or computer-assisted methods. Manual methods involve reading, reviewing, and coding your data by hand using tools such as highlighters, sticky notes, or spreadsheets. Computer-assisted methods involve using software such as QDAcity to organize, manage, and analyze your data electronically.
Step 6:
Report the findings
To report your findings, you need to present your data analysis results in a clear, concise, and coherent manner. You need to describe the main themes, patterns, and meanings that emerged from your data. You need to support your findings with evidence from your data using quotes or examples from your respondents. You also need to discuss the implications and limitations of your findings for your research question, objectives, literature review, and practice. Be sure that, when reporting your findings you present your audit trail, to make your results reproducible and show the rigor of your research methods.
Example of reporting for a qualitative survey
If you are studying the attitudes of college students toward online learning during the COVID-19 pandemic, you could use thematic analysis as a method of data analysis and use QDAcity as a software for organizing and analyzing your data. You can then report on the most prevalent themes of your codesystem in your paper. Be sure to add meaningful quotations that emphasize the importance of each category and present an overview of all the categories with the number of codings in a table.Interview structure in a qualitative survey
A common data collection method in a qualitative survey is an interview. According to Bogner et al. (2014) , an interview can be structured into the following three parts.
(A) Introductory part
- Thanking participant
- Introducing of the interviewer
- Presenting the topic and the motivation
- Informing about general conditions such as the duration about 30 to 90 min (Asking for short-term time constraints)
- Explaining the procedure and the types of questions, informing about the characteristics of semi-structured interviews, about the possibility for additions at any time, about the interest in subjective assessments, opinions and experiences, and about the Opportunity of additions after the interview
- Informing about the data management, Audio data and interview transcripts will be stored separately from contact data, All data will only used for this study
(B) Interview part
- Introductory question: commonly no topic-specific, easy question, positive question, a feel-good question for the interviewee
- Main interview: individual filled by interview questions from the topic blocks
- Last question: open question for additional or missing information (Do you have the impression that we have forgotten any points that are relevant from your point of view? Is there anything else you would like to add?)
(C) Concluding part
- Asking for generally improvements regarding the interview
- Asking for further candidates
- Thanking participants
Conclusion on qualitative surveys as a method in theory-building research
A qualitative survey is a method of collecting data from a large and diverse population using open-ended questions. It can help researchers to explore the opinions, attitudes, experiences and behaviors of the respondents in depth. A qualitative survey should follow four main steps: designing the survey, sampling the population, conducting the survey and code the data. In this article, we have discussed each of these steps in detail and provided some practical tips and examples. We hope that this article will help you to design and conduct your own qualitative survey with confidence and trustworthiness and code your data using QDAcity. Try it out for free.
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